IBM Journey to AI blog

JULY 30, 2024

AI Developer / Software engineers: Provide user-interface, front-end application and scalability support. Organizations in which AI developers or software engineers are involved in the stage of developing AI use cases are much more likely to reach mature levels of AI implementation.

Generative AI 269

Generative AI Data Scientist Software Engineer AI 269

ODSC - Open Data Science

OCTOBER 25, 2024

By leveraging Delphina, teams can significantly reduce the manual work required to set prices, optimize supply chains, prevent fraud, or personalize products, all while keeping data scientists in the driver’s seat, ensuring efficiency without sacrificing control.

Data Scientist 52

Data Scientist Software Engineer Automation AI 52

Unite.AI

MAY 6, 2024

As an AI-powered Digital Engineering enterprise, Persistent has embraced GenAI to revolutionize various aspects of the software engineering lifecycle. Legacy systems often lack comprehensive documentation, hindering the ability of AI to grasp their interdependencies effectively.

Automation 147

Automation Software Engineer Generative AI Software Development 147

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Metadata 134

Metadata Machine Learning Data Scientist Data Quality 134

ODSC - Open Data Science

SEPTEMBER 17, 2024

This talk will also cover the implementation of the RAISE framework, which stands for Responsible AI Security Engineering, designed to provide a step-by-step approach to building secure and resilient AI systems.

LLM 52

LLM Large Language Models Metadata Data Ingestion 52

AWS Machine Learning Blog

NOVEMBER 14, 2024

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. He is focused on AI/ML technology, ML model management, ML governance, and MLOps to improve overall organizational efficiency and productivity.

ML 84

ML Auto-complete Machine Learning Auto-classification 84

Pickl AI

AUGUST 1, 2024

Collaboratio n: Working with data scientists, software engineers, and other stakeholders to integrate Deep Learning solutions into existing systems. Data Quality and Quantity Deep Learning models require large amounts of high-quality, labelled training data to learn effectively.

Deep Learning 52

Deep Learning Neural Network Machine Learning Natural Language Processing 52